Application of oblique projection Krylov subspace method for large scale model reduction

N. Ahmed, M.M. Awais
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引用次数: 1

Abstract

Significant developments have taken place in the area of large-scale matrix computations. Much of these advancements are the result of contributions from Krylov subspace techniques. The popularity of this class of iterative methods in solving large sets of linear and non-linear equations as well as large eigenvalue problems stems from their relative simplicity and generality. Recognizing this property, the paper exploits and introduces the, new mathematical approach, Krylov subspace techniques and their use in the model reduction problem for large-scale systems. Hence the robust control design problem can be solved for the large-scale systems.
斜投影Krylov子空间法在大尺度模型还原中的应用
大规模矩阵计算领域取得了重大进展。这些进步大多是克里洛夫子空间技术贡献的结果。这类迭代方法在求解大型线性和非线性方程组以及大特征值问题方面的流行源于它们的相对简单和通用性。认识到这一性质,本文开发并介绍了新的数学方法——Krylov子空间技术及其在大系统模型约简问题中的应用。从而解决了大型系统的鲁棒控制设计问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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